A team member at Anthropic shared the exact LOOPS.md file Andrej Karpathy uses. When loaded into Claude, it shifted the model from generic replies to responses tailored to the user’s thinking. The approach highlights building a system prompt layer rather than chatting directly with the model.

This GitHub repo by Andrej Karpathy outlines four simple rules in 65 lines that boost AI coding accuracy from 65% to 94%. It covers thinking before coding, keeping implementations minimal, making surgical changes, and defining clear success criteria.

An Anthropic team member shared the internal Claude.md prompt template that Andrej Karpathy uses. Applying this file made Claude stop resisting and deliver exactly the responses the author needed.

Karpathy's observation on human cognitive decline highlights the need for exposure to new and diverse experiences to prevent stagnation in thought and creativity. The author shares personal strategies to maintain mental freshness, such as reading widely and using AI to enhance language and content novelty. Emphasizing the importance of entropy in life, the article advocates for constant novelty to combat predictability and intellectual collapse.